Automate demand forecasting & inventory ordering with AI, MySQL & optimal supplier selection

by sato rio ✓ · 978 views · created 2025-12-26 · Engineering, AI Summarization

What this workflow does

This workflow has 24 nodes and runs on a schedule (every 3 hours). Along the way it connects MySQL and Slack.

How it runs

Trigger: On a schedule (every 3 hours).

1. Fetch POS Data (HTTP Request): calls an HTTP API
2. Fetch Historical Sales (MySQL): select
3. Fetch Weather Forecast (HTTP Request): calls an HTTP API
4. Fetch SNS Trends (HTTP Request): calls an HTTP API
5. Fetch Inventory Master (HTTP Request): calls an HTTP API
6. Merge: merges the data from its input branches
7. Merge: merges the data from its input branches
8. Format Prediction Dataset (Code): runs custom JavaScript code
9. Call AI Prediction API (HTTP Request): calls an HTTP API (POST)
10. Calculate Stock Shortage (Code): runs custom JavaScript code

…plus 13 more steps. See the full node list below.

Services it uses

MySQLSlack

Before you upgrade to n8n 3.0

Nodes used (8)

• Schedule Triggern8n-nodes-base.scheduleTrigger
• HTTP Requestn8n-nodes-base.httpRequest
• MySQLn8n-nodes-base.mySql
• Mergen8n-nodes-base.merge
• Coden8n-nodes-base.code
• Ifn8n-nodes-base.if
• Loop Over Items (Split in Batches)n8n-nodes-base.splitInBatches
• Slackn8n-nodes-base.slack

From the author

This workflow streamlines the entire inventory replenishment process by leveraging AI for demand forecasting and intelligent logic for supplier selection. It aggregates data from multiple sources—POS systems, weather forecasts, SNS trends, and historical…

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